Daily Archives: April 4, 2018

Since their introduction to the United States market in 2006, electronic cigarettes (e-cigarettes) have quickly transformed from a novelty product into a widely used device for the delivery of nicotine and flavored vapors. In 2017, a nationally representative study found that 35.8% of high school seniors reported trying “vaping,” or using e-cigarettes, in comparison to the 26.6% who reported their use of traditional, combustible cigarettes. The study also found that 18.5% of eighth graders reported trying vaping. Youth acceptance of vaping has concerned public health advocates, who worry that the impacts of the successful campaign against tobacco could be reversed if vaping makes young people more likely to initiate smoking.

As of August 1, 2017, 49 states, the District of Columbia, and U.S. federal law regulate e-cigarettes. The Center for Public Health Law Research has released a new dataset analyzing laws controlling electronic cigarettes now available on LawAtlas.org, the Policy Surveillance Program’s website dedicated to empirical legal datasets. This research reveals several important decisions that states make when regulating e-cigarettes.

First is whether e-cigarettes are regulated in the same way as traditional tobacco products. Incorporating e-cigarettes into the existing definition of “tobacco products,” is a common practice. As of August 1, 2017, 11 states and the District of Columbia consider e-cigarettes to be a tobacco product. Additionally, 12 states, the District of Columbia, and U.S. federal law also regulate e-cigarettes similarly to traditional cigarettes by including the use of e-cigarettes in their definition of smoking. This often places e-cigarettes under the control of state clean indoor air acts, which restrict the use of e-cigarettes in the same areas where smoking traditional cigarettes is prohibited.

Another important legal distinction is whether e-cigarettes must contain nicotine. Eleven states and U.S. federal law require an e-cigarette to contain nicotine in order to be legally defined as an e-cigarette. Some e-cigarettes only deliver flavored vapor and do not deliver nicotine. Therefore, definitions of e-cigarettes that require nicotine content do not regulate e-cigarettes that only deliver flavoring. While flavorings may not contain addictive chemicals like nicotine, studies have shown that certain flavoring chemicals can produce harmful reactions in users’ lungs.

The dataset also captures requirements related to online purchasing and product packaging, including child-resistant packaging and nicotine concentration labeling requirements. Child-resistant packaging is important because the nicotine concentrations in the “e-liquids” vaporized by e-cigarettes are high enough to cause nicotine poisoning if ingested or even if touched. Further, online purchasing requirements are important because many e-cigarettes are purchased online and can be shipped to underage users illegally if website vendors are not scrupulous in their screening practices. As of August 1, 2017, 12 states require age verification by a third-party service for online purchases of e-cigarettes.

As medical and scientific researchers continue to publish studies on the potential public health impacts of e-cigarettes, the state regulatory landscape may evolve further. Although many studies conclude that e-cigarettes are less harmful than traditional cigarettes, their long-term effects are still unknown. To aid this research, the new policy surveillance Electronic Cigarette Laws data set serves as a resource for tracking the regulatory response of states as the consumption of e-cigarettes continues to expand.

Imagine a clinical research protocol to test the efficacy of a nutritional regime on the aging trajectory of the participants. Such a study would need to be highly powered and include thousands of people in order to observe a credible effect size. Participants would remain enrolled in the study for many years, maybe decades. Endpoints would include novel measures of healthy aging such as functioning (the capacity to perform certain activities) and the quality of social life. Participants would thus be asked to provide enormous amounts of personal data covering at the same time their health state, their habits and their social activities – most likely with the help of smart appliances, sensor-equipped wearables, mobile phones and electronic records.

In a different scenario a research team aims to develop clinical protocols for cancer treatment according to the unique genomic signature of their tumor. They will need patients, willing to undergo whole genome germline and tumor sequencing right at the moment of diagnosis and be included in a basket trial. Therapy would then be targeted to the specific genetic alterations of each individual in the hope that a combination of targeted drugs would generate better medical outcomes than the current standard of care.

These two scenarios correspond to the prototypical form of, respectively, precision medicine and precision oncology studies. The first is likely to require large (very large) longitudinal cohorts of extensively characterized individuals – like the All of Us Research Program. The second will require sustained sharing of genomic data, information on patients’ clinical history and response to treatment, and possibly a unique repository in which such information would flow to – something akin the NCI’s Genomic Data Common.

This kind of data-intense research, in particular, introduces game changing features: increased uncertainty about foreseeable data uses, expanded temporal span of research activities due to virtually unlimited data lifecycles, and finally, the relational nature of data. This last feature refers both to the fact that, for instance, zip codes contain other types of sensitive information like information about ethnic background (redundant encoding); and to the fact that data about one person contain information about others– as is the case, for instance, with genetic data among family members. Continue reading →

Decision aids can be highly-effective tools to promote shared decision making and support patients in becoming engaged participants in their healthcare. Join us for the first-ever convening with leaders behind a Washington experiment in certifying decision aids, as state officials, health systems, and on-the-ground implementation experts share lessons learned and discuss policy recommendations for national or statewide approaches to decision aid certification.

Program Overview

Person-centered care presents a unique opportunity to achieve the Quadruple Aim, especially during serious illness when people are the most vulnerable. Building on the work of NQF and others, it is now clear that healthcare purchasers (states, plans, care providers) committed to person-centered care should also be committed to shared decision-making.

A number of policy initiatives have sought to increase the use of decision aids as an effective way to further shared decision making and person-centered care. Washington is the first – and so far only – state to recognize and act on this opportunity by establishing a process to certify decision aids across the health continuum, including during serious illness when people are the most vulnerable. The program will examine the Washington experience and also explore policy barriers for replication of the Washington model at the state and national levels.

This event is free and open to the public, but seating is limited and registration is required. Register now!

This event is part of the Project for Advanced Care and Health Policy, a collaboration between the Petrie-Flom Center and the Coalition to Transform Advanced Care (C-TAC), a non-partisan, non-profit alliance of over 130 national organizations dedicated to being a catalyst to change the health delivery system, empower consumers, enhance provider capacity and improve public and private policies in advanced illness care.